{"id":"W3096628046","doi":"10.3390/met10111420","title":"Decrease of Nozzle Clogging through Fluid Flow Control","year":2020,"lang":"en","type":"article","venue":"Metals","topic":"Metallurgical Processes and Thermodynamics","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Clogging; Nozzle; Mechanics; Deposition (geology); Boundary (topology); Volumetric flow rate; Materials science; Flow (mathematics); Impurity; Petroleum engineering; Engineering; Mechanical engineering; Mathematics; Geology; Chemistry; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008653232,0.0001203451,0.0003111419,0.00001326183,0.00001764648,0.00001165974,0.0001321055,0.0000456713,0.0005457112],"category_scores_gemma":[0.0001093231,0.0000999245,0.0001110891,0.0001212924,0.00002195454,0.0001080693,0.00001817481,0.00007977096,0.00008371963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007808297,"about_ca_system_score_gemma":0.000008740835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005010141,"about_ca_topic_score_gemma":0.00000101446,"domain_scores_codex":[0.9993476,0.00001835009,0.0002378657,0.0001175936,0.0001214919,0.0001571601],"domain_scores_gemma":[0.9996408,0.00005523192,0.00002956481,0.0001268953,0.00002618694,0.0001212736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006607837,0.00005876358,0.00001614519,0.0006531201,0.0004707428,0.00002496707,0.0005281575,0.8668905,0.114997,0.01023605,0.0005889995,0.005469413],"study_design_scores_gemma":[0.0004520966,0.00002196863,0.00001217741,0.000009302447,0.00005961956,0.000001711474,0.0000139023,0.9767455,0.005891957,0.0007921711,0.01588287,0.0001167514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1340653,0.002981732,0.8480822,0.0003855329,0.0001349632,0.0001735124,0.00003869093,0.0002584438,0.01387963],"genre_scores_gemma":[0.9951854,0.00007669315,0.004140784,0.0004519165,0.00008333436,0.000006639405,0.000006424483,0.00002611133,0.00002264997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8611202,"threshold_uncertainty_score":0.5975155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01615795454661194,"score_gpt":0.216491395662858,"score_spread":0.2003334411162461,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}